A multiplex qPCR assay for the identification of Pinus palustris and Pinus elliottii

Authors

  • Mohamad Miftah Rahman Department of Sustainable Bioproducts, Mississippi State University
  • Adriana Costa Mississippi State University
  • Frank C. Owens Department of Sustainable Bioproducts, Mississippi State University
  • Alex C. Wiedenhoeft Center for Wood Anatomy Research, USDA Forest Products Laboratory, Madison, WI

Abstract

Differentiating the wood of high-strength southern yellow pines (Pinus palustris and P. elliottii) from their lower-strength congeners (P. taeda and P. echinata) presents a substantial challenge once diagnostic external features, such as needles, cones, and bark are absent. This difficulty arises from their wood anatomical indistinguishability and low genetic resolution driven by highly conserved genome organization and extensive allele sharing. To address this, we developed and validated a multiplex qPCR assay utilizing SYBR Green chemistry and asymmetric primer concentrations, working with leaf and seed DNA. The assay targets short amplicons (<100 bp) to maximize the likelihood of amplification of the fragmented DNA typical of solid wood. The method achieved high linearity (R² > 0.99) and efficiency, successfully co-amplifying targets while maintaining clear discrimination through distinct mean melting temperatures (77.98°C [SD 0.11] and 69.25°C [SD 0.26], respectively). Sensitivity testing established limits of detection at 1 pg for Pinus palustris and 10 pg for Pinus elliottii. Validation across a panel of 84 individuals representing all four species yielded 100% accuracy, precision, and recall. This study establishes a rapid, gel-free molecular diagnostic tool that overcomes the limitations of wood anatomical identification. By validating a short-amplicon design on leaf and seed tissues, it provides a proof-of-concept for future applications on solid wood and offers a reproducible methodological framework for species verification.

References

Barnett JP (2019) Naval Stores: A History of an Early Industry Created from the South’s Forests. General Technical Report SRS-240. USDA Forest Service, Southern Research Station, Asheville, NC, USA. https://doi.org/10.2737/SRS-GTR-240

Bell G (2016) Replicates and repeats. BMC Biol 14(28). https://doi.org/10.1186/s12915-016-0254-5

Borland EM, Kading RC (2021) Modernizing the toolkit for arthropod bloodmeal identification. Insects 12(1):37. https://doi.org/10.3390/insects12010037

Broeders S, Huber I, Grohmann L, Berben G, Taverniers I, Mazzara M, Roosens N, Morisset D (2014) Guidelines for validation of qualitative real-time PCR methods. Trends Food Sci Technol 37(2):115–126. https://doi.org/10.1016/j.tifs.2014.03.008

Brunner AM, Yakovlev IA, Strauss SH (2004) Validating internal controls for quantitative plant gene expression studies. BMC Plant Biol 4. https://doi.org/10.1186/1471-2229-4-14

Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, Mueller R, Nolan T, Pfaffl MW, Shipley GL, Vandesompele J, Wittwer CT (2009) The MIQE guidelines: Minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55(4):611–622. https://doi.org/10.1373/clinchem.2008.112797

Bustin SA, Kirvell S, Nolan T, Mueller R, Shipley GL (2025) When two-fold is not enough: quantifying uncertainty in lowcCopy qPCR. Int J Mol Sci 26(16):7796. https://doi.org/10.3390/ijms26167796

Chabi J, Van’t Hof A, N’dri LK, Datsomor A, Okyere D, Njoroge H, Pipini D, Hadi MP, De Souza DK, Suzuki T, Dadzie SK, Jamet HP (2019) Rapid high throughput SYBR green assay for identifying the malaria vectors Anopheles arabiensis, Anopheles coluzzii and Anopheles gambiae s.s. Giles. PLoS One 14(4). https://doi.org/10.1371/journal.pone.0215669

Chen J, Tauer CG, Huang Y (2002) Paternal chloroplast inheritance patterns in pine hybrids detected with trnL-trnF intergenic region polymorphism. Theoretical and Applied Genetics 104(8):1307–1311. https://doi.org/10.1007/s00122-002-0893-5

Costa A, Giraldo G, Bishell A, He T, Kirker G, Wiedenhoeft AC (2022) Organellar microcapture to extract nuclear and plastid DNA from recalcitrant wood specimens and trace evidence. Plant Methods 18(51). https://doi.org/10.1186/s13007-022-00885-z

Davy CM, Kidd AG, Wilson CC (2015) Development and validation of environmental DNA (eDNA) markers for detection of freshwater turtles. PLoS One 10(7): e0130965. https://doi.org/10.1371/journal.pone.0130965

Debode F, Marien A, Janssen É, Bragard C, Berben G (2017) The influence of amplicon length on real-time PCR results. BASE 21(1). https://doi.org/10.25518/1780-4507.13461

Demeke T, Jenkins GR (2010) Influence of DNA extraction methods, PCR inhibitors and quantification methods on real-time PCR assay of biotechnology-derived traits. Anal Bioanal Chem 396:1977–1990. https://doi.org/10.1007/s00216-009-3150-9

Die JV, Roman B, Flores F, Rowland LJ (2016) Design and sampling plan optimization for RT-qPCR experiments in plants: A case study in blueberry. Front Plant Sci 7(MAR2016). https://doi.org/10.3389/fpls.2016.00271

Dormontt EE, Boner M, Braun B, Breulmann G, Degen B, Espinoza E, Gardner S, Guillery P, Hermanson JC, Koch G, Lee SL, Kanashiro M, Rimbawanto A, Thomas D, Wiedenhoeft AC, Yin Y, Zahnen J, Lowe AJ (2015) Forensic timber identification: It’s time to integrate disciplines to combat illegal logging. Biol Conserv 191:790–798. https://doi.org/10.1016/j.biocon.2015.06.038

Drouin G, Daoud H, Xia J (2008) Relative rates of synonymous substitutions in the mitochondrial, chloroplast and nuclear genomes of seed plants. Mol Phylogenet Evol 49(3):827–831. https://doi.org/10.1016/j.ympev.2008.09.009

Dumolin-Lapegue S, Pemonge MH, Petit RJ (1997) An enlarged set of consensus primers for the study of organelle DNA in plants. Mol Ecol 6:393–397. https://doi.org/10.1046/j.1365-294X.1997.00193.x

Dwight Z, Palais R, Wittwer CT (2011) uMELT: Prediction of high-resolution melting curves and dynamic melting profiles of PCR products in a rich web application. Bioinformatics 27(7):1019–1020. https://doi.org/10.1093/bioinformatics/btr065

Eberhardt TL, Lebow PK, Sheridan PM, Bhuta AAR (2022) Identifying southern yellow pine cross sections from the southeastern United States using quadratic discriminant analysis on pith and second annual ring diameters. Dendrochronologia (Verona) 71:125904. https://doi.org/10.1016/j.dendro.2021.125904

Eckert AJ, Van Heerwaarden J, Wegrzyn JL, Nelson CD, Ross-Ibarra J, González-Martínez SC, Neale DB (2010) Patterns of population structure and environmental associations to aridity across the range of loblolly pine (Pinus taeda L., Pinaceae). Genetics 185(3):969–982. https://doi.org/10.1534/genetics.110.115543

Entsminger ED, Brashaw BK, Seale RD, Ross RJ (2020) Machine grading of lumber—practical concerns for lumber producers. General Technical Report FPL-GTR-279. USDA Forest Service, Forest Products Lab, Madison, WI USA. https://research.fs.usda.gov/treesearch/61781

Fang S, Yan X, Liao H (2009) 3D reconstruction and dynamic modeling of root architecture in situ and its application to crop phosphorus research. Plant Journal 60(6):1096-1108. https://doi.org/10.1111/j.1365-313X.2009.04009.x

Forootan A, Sjöback R, Björkman J, Sjögreen B, Linz L, Kubista M (2017) Methods to determine limit of detection and limit of quantification in quantitative real-time PCR (qPCR). Biomol Detect Quantif 12 (June): 1-6. https://doi.org/10.1016/j.bdq.2017.04.001

Gaby LI (1985) Southern pines : loblolly pine (Pinus taeda L.), longleaf pine (Pinus palustris Mill.), shortleaf pine (Pinus echinata Mill.), slash pine (Pinus elliottii Engelm.). FS-256 USDA Forest Service, Southeastern Forest Experiment Station, Forestry Sciences Lab, Athens, GA USA. https://research.fs.usda.gov/treesearch/32196

Galligan W, Snodgrass D, Crow G (1977) Machine stress rating: practical concerns for lumber producers. General Technical Report FPL; 7. USDA Forest Service, Forest Products Lab Madison, WI USA. https://babel.hathitrust.org/cgi/pt?id=umn.31951d02988572n&seq=6

Gernandt DS, Geada López G, Ortiz García S, Liston A (2005) Phylogeny and classification of Pinus. Taxon 54(1):29-42. https://doi.org/10.2307/25065300

Gómez-Zeledón J, Grasse W, Runge F, Land A, Spring O (2017) TaqMan qPCR pushes boundaries for the analysis of millennial wood. J Archaeol Sci 79:53-61. https://doi.org/10.1016/j.jas.2017.01.010

Gualberto JM, Newton KJ (2017) Plant mitochondrial genomes: Dynamics and mechanisms of mutation. Annu Rev Plant Biol 68:225-252. https://doi.org/10.1146/annurev-arplant-043015-112232

Hollingsworth PM, Graham SW, Little DP (2011) Choosing and using a plant DNA barcode. PLoS One 6(5): e19254. https://doi.org/10.1371/journal.pone.0019254

Höltken A, Schröder H, Wischnewski N, Degen B, Magel E, Fladung M (2012) Development of DNA-based methods to identify CITES-protected timber species: a case study in the Meliaceae family. Holzforschung 66(1). https://doi.org/10.1515/HF.2011.142

Hoorfar J, Malorny B, Abdulmawjood A, Cook N, Wagner M, Fach P (2004) Practical considerations in design of internal amplification controls for diagnostic PCR assays. J Clin Microbiol 42(5). https://doi.org/10.1128/jcm.42.5.1863-1868.2004

Howard ET, Manwiller FG (1969) Anatomical characteristics of southern pine stemwood. Wood Science 2(2):77-86. https://eurekamag.com/research/014/345/014345190.php

Huber I, Block A, Sebah D, Debode F, Morisset D, Grohmann L, Berben G, Štebih D, Milavec M, Žel J, Busch U (2013) Development and validation of duplex, triplex, and pentaplex real-time PCR screening assays for the detection of genetically modified organisms in food and feed. J Agric Food Chem 61(43):10293–10301. https://doi.org/10.1021/jf402448y

Jackman SD, Coombe L, Warren RL, Kirk H, Trinh E, MacLeod T, Pleasance S, Pandoh P, Zhao Y, Coope RJ, Bousquet J, Bohlmann J, Jones SJM, Birol I (2020) Complete mitochondrial genome of a gymnosperm, sitka spruce (Picea sitchensis), indicates a complex physical structure. Genome Biol Evol 12(7):1174–1179. https://doi.org/10.1093/GBE/EVAA108

Jiao L, Yin Y, Cheng Y, Jiang X (2014) DNA barcoding for identification of the endangered species Aquilaria sinensis: Comparison of data from heated or aged wood samples. Holzforschung 68(4). https://doi.org/10.1515/hf-2013-0129

Jiao L, Yin Y, Xiao F, Sun Q, Song K, Jiang X (2012) Comparative analysis of two DNA extraction protocols from fresh and dried wood of Cunninghamia lanceolata (Taxodiaceae). IAWA J 33(4): 441-456. https://doi.org/10.1163/22941932-90000106

Jin WT, Gernandt DS, Wehenkel C, Xia XM, Wei XX, Wang XQ (2021) Phylogenomic and ecological analyses reveal the spatiotemporal evolution of global pines. Proc Natl Acad Sci U S A 118(20): e2022302118. https://doi.org/10.1073/PNAS.2022302118

Katoh K, Standley DM (2013) MAFFT multiple sequence alignment software version 7: Improvements in performance and usability. Mol Biol Evol 30(4): 772–780. https://doi.org/10.1093/molbev/mst010

Koch P (1972) Utilization of the Southern Pines, 420th edn. USDA-Forest Service, Southern Forest Experiment Station, Asheville, NC. https://research.fs.usda.gov/treesearch/40211

Kontanis EJ, Reed FA (2006) Evaluation of real-time PCR amplification efficiencies to detect PCR inhibitors. J Forensic Sci 51(4):795-804. https://doi.org/10.1111/j.1556-4029.2006.00182.x

Kralik P, Ricchi M (2017) A basic guide to real time PCR in microbial diagnostics: Definitions, parameters, and everything. Front Microbiol 8:108. https://doi.org/10.3389/fmicb.2017.00108

Kukachka BF (1960) Identification of Coniferous Woods. TAPPI 43(11):887–896. https://research.fs.usda.gov/treesearch/25674

Lee SY, Ng WL, Mohamed R (2016) Rapid species identification of highly degraded agarwood products from Aquilaria using real-time PCR. Conserv Genet Resour 8(4):581–585. https://doi.org/10.1007/s12686-016-0599-7

Liu ZF, Ma H, Ci XQ, Li L, Song Y, Liu B, Li HW, Wang SL, Qu XJ, Hu JL, Zhang XY, Conran JG, Twyford AD, Yang JB, Hollingsworth PM, Li J (2021) Can plastid genome sequencing be used for species identification in Lauraceae? Bot J Linn Soc 197(1):1–14. https://doi.org/10.1093/botlinnean/boab018

Mohamed R, Tan HY, Siah CH (2012) A real-time PCR method for the detection of trnL-trnF sequence in agarwood and products from Aquilaria (Thymelaeaceae). Conserv Genet Resour 4(3):803–806. https://doi.org/10.1007/s12686-012-9648-z

Naeem MA, Ijaz F, Amir M, Aftab RK (2024) SYBR Green PCR is cost-effective for detecting genetic abnormalities in acute myeloid leukemia. J Haematol Stem Cell Res 4(2):234–237. https://jhscr.org/index.php/JHSCR/article/view/132

Neale DB, Sederoff RR (1989) Paternal inheritance of chloroplast DNA and maternal inheritance of mitochondrial DNA in loblolly pine. Theor Appl Genet 77(2): 212–216. https://doi.org/10.1007/BF00266189

Neale DB, Wegrzyn JL, Stevens KA, Zimin AV, Puiu D, Crepeau MW, Cardeno C, Koriabine M, Holtz-Morris AE, Liechty JD, Martínez-García PJ, Vasquez-Gross HA, Lin BY, Zieve JJ, Dougherty WM, Fuentes-Soriano S, Wu LS, Gilbert D, Marçais G, Roberts M, Holt C, Yandell M, Davis JM, Smith KE, Dean JFD, Lorenz WW, Whetten RW, Sederoff R, Wheeler N, McGuire PE, Main D, Loopstra CA, Mockaitis K, deJong PJ, Yorke JA, Salzberg SL, Langley CH (2014) Decoding the massive genome of loblolly pine using haploid DNA and novel assembly strategies. Genome Biol 15(R59). https://doi.org/10.1186/gb-2014-15-3-r59

Olatinwo R, Jackson DP, Sung S-JS, Mangini A, Strom B, Barnett JP (2020) Genetic markers for identification of southern pine species. In: Proceedings of the 20th Biennial Southern Silvicultural Research Conference, e–Gen. Tech. Rep. SRS–253. USDA Forest Service, Southern Research Station, Asheville, NC USA. https://research.fs.usda.gov/treesearch/61549

Panshin AJ, Zeeuw C de (1980) Textbook of wood technology. Volume I. Structure, identification, uses, and properties of the commercial woods of the United States and Canada. McGraw-Hill, New York.

Ponchel F, Toomes C, Bransfield K, Leong FT, Douglas SH, Field SL, Bell SM, Combaret V, Puisieux A, Mighell AJ, Robinson PA, Inglehearn CF, Isaacs JD, Markham AF (2003) Real-time PCR based on SYBR-Green I fluorescence: An alternative to the TaqMan assay for a relative quantification of gene rearrangements, gene amplifications and micro gene deletions. BMC Biotechnol 3(18). https://doi.org/10.1186/1472-6750-3-18

Potter KM, Hipkins VD, Mahalovich MF, Means RE (2013) Mitochondrial DNA haplotype distribution patterns in Pinus ponderosa (Pinaceae): Range-wide evolutionary history and implications for conservation. Am J Bot 100(8):1562-1579. https://doi.org/10.3732/ajb.1300039

Powell W, Morgante M, McDevitt R, Vendramin GG, Rafalski JA (1995) Polymorphic simple sequence repeat regions in chloroplast genomes: Applications to the population genetics of pines. PNAS 92(17):7759-7763. https://doi.org/10.1073/pnas.92.17.7759

Rachmayanti Y, Leinemann L, Gailing O, Finkeldey R (2009) DNA from processed and unprocessed wood: Factors influencing the isolation success. Forensic Sci Int Genet 3(3):p185-192. https://doi.org/10.1016/j.fsigen.2009.01.002

Regmi A, Grebner DL, Willis JL, Grala RK (2022) Price premium requirements for growing higher quality pine sawtimber in even-aged systems in the Southeastern United States. J For 120(2):133–144. https://doi.org/10.1093/jofore/fvab048

Ririe KM, Rasmussen RP, Wittwer CT (1997) Product differentiation by analysis of DNA melting curves during the polymerase chain reaction. Anal Biochem 245(2): 154-160. https://doi.org/10.1006/abio.1996.9916

Ross RJ (2015) Nondestructive evaluation of wood: second edition. General Technical Report 10.2737/FPL-GTR-238. USDA Forest Service, Forest Products Lab, Madison, WI USA. https://doi.org/10.2737/FPL-GTR-238

Rowan BA, Oldenburg DJ, Bendich AJ (2009) A multiple-method approach reveals a declining amount of chloroplast DNA during development in Arabidopsis. BMC Plant Biol 9(3). https://doi.org/10.1186/1471-2229-9-3

Safdar M, Junejo Y (2015) Development and validation of fast duplex real-time PCR assays based on SYBER Green fluorescence for detection of bovine and poultry origins in feedstuffs. Food Chem 173: 660-664. https://doi.org/10.1016/j.foodchem.2014.10.088

Sakamoto W, Takami T (2018) Chloroplast DNA dynamics: Copy number, quality control and degradation. Plant Cell Physiol 59(6):1120–1127. https://doi.org/10.1093/pcp/pcy084

Sarkar SL, Alam ASMRU, Das PK, Pramanik MHA, Al-Emran HM, Jahid IK, Hossain MA (2022) Development and validation of cost-effective one-step multiplex RT-PCR assay for detecting the SARS-CoV-2 infection using SYBR Green melting curve analysis. Sci Rep 12(6501). https://doi.org/10.1038/s41598-022-10413-7

Särkinen T, George M (2013) Predicting plastid marker variation: Can complete plastid genomes from closely related species help? PLoS One 8(11). https://doi.org/10.1371/journal.pone.0082266

Schrader C, Schielke A, Ellerbroek L, Johne R (2012) PCR inhibitors - occurrence, properties and removal. J Appl Microbiol 113(5):1014–1026. https://doi.org/10.1111/j.1365-2672.2012.05384.x

Senalik CA, Farber B (2021) Mechanical properties of wood. In: Wood handbook—wood as an engineering material. U.S. Department of Agriculture, Forest Service, Forest Products Laboratory, Wisconsin. https://research.fs.usda.gov/treesearch/62244

Tajadini M, Panjehpour M, Javanmard S (2014) Comparison of SYBR Green and TaqMan methods in quantitative real-time polymerase chain reaction analysis of four adenosine receptor subtypes. Adv Biomed Res 3(1):85. https://doi.org/10.4103/2277-9175.127998

Taylor S, Wakem M, Dijkman G, Alsarraj M, Nguyen M (2010) A practical approach to RT-qPCR-Publishing data that conform to the MIQE guidelines. Methods 50(4):S1-S5. https://doi.org/10.1016/j.ymeth.2010.01.005

Watanabe U, Abe H, Yoshida K, Sugiyama J (2015) Quantitative evaluation of properties of residual DNA in Cryptomeria japonica wood. Journal of Wood Science 61:1–9. https://doi.org/10.1007/s10086-014-1447-6

Western Wood Products Association (2008) Western Lumber Product Use Manual. https://wwpastore.org/products/western-lumber-products-use-manual

Wolfe KH, Li WH, Sharp PM (1987) Rates of nucleotide substitution vary greatly among plant mitochondrial, chloroplast, and nuclear DNAs. PNAS 84(24). https://doi.org/10.1073/pnas.84.24.9054

Wu J, Krutovskii KV, Strauss SH (1998) Abundant mitochondrial genome diversity, population differentiation and convergent evolution in pines. Genetics 150(4):1605–1614. https://doi.org/10.1093/genetics/150.4.1605

Xia Q, Zhang H, LvD, El-Kassaby YA, Li W (2023) Insights into phylogenetic relationships in Pinus inferred from a comparative analysis of complete chloroplast genomes. BMC Genomics 24(346). https://doi.org/10.1186/s12864-023-09439-6

Zhou X, Zhang T, Song D, Huang T, Peng Q, Chen Y, Li A, Zhang F, Wu Q, Ye Y, Tang Y (2017) Comparison and evaluation of conventional RT-PCR, SYBR green I and TaqMan real-time RT-PCR assays for the detection of porcine epidemic diarrhea virus. Mol Cell Probes 33:36-41. https://doi.org/10.1016/j.mcp.2017.02.002

Zimin A, Stevens KA, Crepeau MW, Holtz-Morris A, Koriabine M, Marçais G, Puiu D, Roberts M, Wegrzyn JL, de Jong PJ, Neale DB, Salzberg SL, Yorke JA, Langley CH (2014) Sequencing and assembly of the 22-Gb loblolly pine genome. Genetics 196(3):875–890. https://doi.org/10.1534/genetics.113.159715

Published

2026-07-20

Issue

Section

Research Contributions